DetectAreasMode
Inheritance: java.lang.Object, java.lang.Enum
public enum DetectAreasMode extends Enum<DetectAreasMode>
Fields
| Field | Description |
|---|---|
| COMBINE | Detects paragraphs with text and then uses another NN model to detect areas inside paragraphs. |
| CURVED_TEXT | Automatically straightens curved lines of text in the image, improving recognition accuracy and allowing more text to be recovered and extracted. |
| DOCUMENT | Detects paragraphs using NN model for documents. |
| LEAN | Prioritizes speed and reduces resource consumption by omitting support for complex layouts. |
| MULTICOLUMN | Detects large blocks of text formatted in columns. |
| NONE | Doesn’t detect paragraphs. |
| PHOTO | Detects paragraphs using NN model for photos. |
| TABLE | Detects tabular structures in the image and extracts text from individual cells. |
| TEXT_IN_WILD | A specialized neural network for extracting words from low-quality images such as street photos, license plates, passport photos, meter photos, and photos with noisy backgrounds. |
| UNIVERSAL | Detects all blocks of text in the image, including sparse and irregular text on photos. |
Methods
COMBINE
public static final DetectAreasMode COMBINE
Detects paragraphs with text and then uses another NN model to detect areas inside paragraphs. Better for images with a complex structure.
CURVED_TEXT
public static final DetectAreasMode CURVED_TEXT
Automatically straightens curved lines of text in the image, improving recognition accuracy and allowing more text to be recovered and extracted. Requires significant processing power and RAM.
DOCUMENT
public static final DetectAreasMode DOCUMENT
Detects paragraphs using NN model for documents. Better for multicolumn documents or documents with pictures or non-text objects.
LEAN
public static final DetectAreasMode LEAN
Prioritizes speed and reduces resource consumption by omitting support for complex layouts. Suitable only for simple images with a few lines of text without illustrations or formatting.
MULTICOLUMN
public static final DetectAreasMode MULTICOLUMN
Detects large blocks of text formatted in columns. Best choice for multi-column layouts such as book pages, articles, or contracts.
NONE
public static final DetectAreasMode NONE
Doesn’t detect paragraphs. Better for a simple one-column document without pictures.
PHOTO
public static final DetectAreasMode PHOTO
Detects paragraphs using NN model for photos. Better for images with a lot of pictures and non-text objects.
TABLE
public static final DetectAreasMode TABLE
Detects tabular structures in the image and extracts text from individual cells. Recommended for scanned spreadsheets, reports, and other table-based documents.
TEXT_IN_WILD
public static final DetectAreasMode TEXT_IN_WILD
A specialized neural network for extracting words from low-quality images such as street photos, license plates, passport photos, meter photos, and photos with noisy backgrounds.
UNIVERSAL
public static final DetectAreasMode UNIVERSAL
Detects all blocks of text in the image, including sparse and irregular text on photos. A versatile option for most images, except for tables and multi-column layouts.